ABSTRACT An estimated 53% of U.S. adults have dyslipidemia, putting a majority of the U.S. adult population at high risk for related chronic diseases such as cardiovascular diseases, non-alcoholic fatty liver disease, and gallbladder disease. US Hispanic/Latinos (H/L) ages 18?74 have an overall prevalence of dyslipidemia of 65%, among the highest reported in the US. Lipid traits are highly heritable; estimates range from 20 to 70%, with common genetic variants explaining ~30% of the variance for these traits in Europeans. As serum concentrations of lipids are established therapeutic targets for many lipid-related chronic diseases, researchers have invested considerable effort into understanding the genetic epidemiology of lipid traits, however these large-scale efforts have almost exclusively considered Caucasians. Understudied at-risk populations provide a powerful design to gain insight into genetic mechanisms for disease because they can exhibit finer haplotypic structure and have different underlying causal variants. To ensure ancestrally diverse populations are not the last to benefit from the new era of precision medicine, we must both increase representation of ancestrally diverse populations in genetic research and develop expedited strategies for translating genomics for clinical utility. First, to enrich discovery, we will conduct the first large-scale GWAS and rare variant analyses for lipid- related traits in H/L. We will meta-analyze, fine-map, perform multivariate associations, and validate effects in all available H/L samples in analyses that will include >50,000 samples. Second, to interpret function, we will move GWAS findings into an interpretable biological context and characterize the regulatory mechanisms involved in lipid regulation via tissue-specific functional analysis, and ancestry-specific validation of effects using RNAseq data in two independent H/L cohorts. Identification of genes and pathways associated with lipid levels elucidates important basic biology about human metabolism, but isn?t necessarily clinically translatable. Thus, to evaluate clinical significance of lipid-associated genetic risk factors, we will use multiple massive genetic and electronic medical record repositories (including the Multiethnic Cohort, BioME, and BioVU) to identify clinical outcomes associated with single variants and genetically regulated expression of lipid- associated genes in H/L phenome-wide. Our design focuses effort on discovery of new variants and loci by pioneering genetic studies of lipid-related traits in diverse H/L populations, functional interpretation of variant effects via gene-based annotation and expression prediction with robust validation, and characterizing the clinical outcomes predicted by lipid-associated genetics in three large DNA bio-banks with linked electronic medical records. These population-specific, function- and outcome-oriented approaches will advance understanding of the genetic etiology of lipids and related traits with high H/L disparities of risk, revealing new biologic pathways and providing new avenues for precision treatment for H/L, a population that will constitute ~35% of the US population by the year 2050.